Millions of adults have chronic kidney disease (CKD), leading to substantial morbidity, mortality and health care costs. These effects are concentrated in patients with high-risk disease. Several provider- and system-level barriers lead to well-described gaps in care for these patients, contributing to poor outcomes. Given the growing CKD population, the relative dearth of nephrologists, and the fragmented care that high-risk patients receive, novel tools are needed to improve the quality and safety of CKD care and clinical outcomes. Population health management (PHM) improves health by aggregating and analyzing data across a population to drive consistent, evidence-based care. CKD PHM using electronic health records (EHRs) can be a sustainable strategy to overcome physician- and system-level barriers. EHR-based PHM could improve the identification of patients with high-risk CKD; increase the use of evidence-based, widely available, and cost- effective interventions; and enhance medication safety. We have developed the tools needed to implement and examine the impact of an EHR-based PHM intervention. Our multidisciplinary team has constructed a dynamic CKD registry containing real-time data and embedded metrics for identifying high-risk CKD using validated risk-prediction models, reviewing medication exposures, and monitoring processes of care. We have successfully leveraged this tool to pilot an EHR-based PHM intervention that targets the timely detection of high-risk CKD, the implementation of remote nephrology guidance to improve evidence-based CKD care, and the provision of medication safety reviews and standardized CKD patient education. The overarching aim of this proposal is to test the effectiveness of a multifaceted EHR-based PHM intervention to improve the delivery of evidence-based CKD care in high-risk patients. The University of Pittsburgh's extensive PCP network offers the ideal setting to evaluate the intervention with 330 PCPs caring for over 480,000 patients while using the Epic EHR. We will perform a 42-month pragmatic, cluster randomized controlled trial in ~1,700 patients with high-risk CKD managed by their PCPs to determine whether EHR-based PHM improves key processes of care and clinical outcomes. We hypothesize that EHR-based PHM will improve hypertension control, use of renin angiotensin aldosterone system inhibitors in patients with albuminuria, and avoidance of renally contraindicated medications (Aim 1) and delay CKD progression (Aim 2). This novel intervention benefits from customization based on PCP stakeholder feedback, executive level support from the medical center and health plan, and enthusiastic support from PCPs. This study directly responds to calls from national primary care organizations to use EHRs to implement PHM while limiting the PCP burden. CKD PHM may provide a sustainable, resourceful approach to improving CKD care, outcomes, and safety. In addition, our pragmatic cluster RCT will produce code for PHM dashboards in the most widely adopted ambulatory EHR in the US, facilitating dissemination and a potential transformation in CKD care.